Method of and system for calibration of inspection systems producing x-ray images

ABSTRACT

According to one embodiment, a calibration system for calibrating image data produced by an imaging system is provided. The calibration system includes a processor configured for: receiving the image data from the imaging system; receiving a plurality of reference values from the imaging system; and calibrating the image data using the reference values. The reference values correspond to air image data produced by the imaging system.

CROSS-REFERENCE TO RELATED PATENT APPLICATIONS

This application claims priority to U.S. Provisional Patent ApplicationNo. 61/032,906, filed on Feb. 29, 2008, and U.S. Provisional PatentApplication No. 61/036,636, filed on Mar. 14, 2008, the contents of allof which are incorporated herein by reference in their entirety.

BACKGROUND OF THE INVENTION

Embodiments of the present invention relate generally to calibration ofsystems for inspecting electronic assemblies such as, but not limitedto, circuit cards and printed circuit boards (PCBs).

An X-ray system may be used to inspect such assemblies. For example, aPCB on which a ball grid array (BGA) is present may be inspected fordefects. Such defects may include portions of the BGA where solder didnot reflow properly during manufacturing and/or where the solder reflowprocess was similarly deficient or otherwise insufficient. As a result,defects such as bridges and ball-and-socket-type opens may be present.

One metric used to measure performance of an inspection system orprocess is the so-called “false calls” rate. This metric reflects thenumber of times an acceptable (or non-defective) joint of an assembly isincorrectly or unnecessarily identified as being unacceptable (ordefective) during inspection. For example, in one scenario, anacceptable joint is incorrectly identified as being unacceptable by onesystem. However, the same joint is correctly identified as beingacceptable by another system. The incorrect identification by the firstsystem is an example of an occurrence that would result in an increaseof the false calls rate. Ideally, the first system should haveidentified the acceptable joint as being acceptable, thereby preemptingan increase of the false calls rate. To improve efficiency, the accuracyof inspection systems should be improved such that the false calls rateis decreased.

Calibration of inspection systems, such as the system described above,may be performed to provide various features. For example, as describedabove, such systems may be calibrated to improve stability and/orconsistency across results provided by different systems. In addition,calibration may be used to improve stability, reproducibility and/orconsistency across results provided at different times by a same system(for example, inspections performed over the operational lifetime(s) ofone or more parts or portions of the system). Furthermore, calibrationmay be performed such that adverse effects of so-called “systematicerrors” (i.e., repeatable errors that can be removed throughcalibration) are effectively removed or dampened. Such systematic errorsmay be caused, for example, by geometrical deficiencies, defects (orother imperfections) in system design, performance characteristics ofsystem parts (e.g., the X-ray source and/or detection sensors), andother non-ideal operating conditions. Those skilled in the art willappreciate that the performance of an X-ray system may be negativelyaffected by both systematic errors and random noise.

SUMMARY OF THE INVENTION

An aspect of embodiments of the present invention is directed tominimizing (or reducing) the effects of systematic errors on thestability, reproducibility and consistency of imaging devices (orsystems) such as, but not limited to, inspection devices. The inspectiondevices may use X-ray energy to generate the images.

According to one embodiment, a calibration system for calibrating imagedata produced by an imaging system is provided. The calibration systemincludes a processor configured for: receiving the image data from theimaging system; receiving a plurality of reference values from theimaging system; and calibrating the image data using the referencevalues. The reference values correspond to air image data produced bythe imaging system.

According to another embodiment, a calibration system for calibratingimage data produced by an imaging system is provided. The calibrationsystem includes means for receiving the image data from the imagingsystem; means for receiving a plurality of reference values from theimaging system; and means for calibrating the image data using thereference values. The reference values correspond to air image dataproduced by the imaging system.

According to another embodiment, a method for calibrating image dataproduced by an imaging device is provided. The method includes:receiving the image data from the imaging device; receiving a pluralityof reference values from the imaging device; and calibrating the imagedata using the reference values. The reference values correspond to airimage data produced by the imaging device.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows an inspection system according to one embodiment.

FIG. 2 shows an inspection system according to another embodiment.

FIG. 3A shows a calibration system according to one embodiment.

FIG. 3B shows a calibration system according to another embodiment.

FIG. 4 shows a calibration flowchart according to a known system.

FIG. 5 shows a calibration flowchart of a generalized inverse logtransform (GILT) process according to one embodiment.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Embodiments of the present invention are directed to calibration ofsystems for inspecting electronic assemblies such as, but not limitedto, circuit cards and printed circuit boards (PCBs). In particularembodiments, the systems may be used to inspect PCBs on which ball gridarrays (BGAs) are present. In particular embodiments, the system is anX-ray inspection system, for example, operated according to atomosynthesis imaging technique. Such a technique is disclosed in U.S.Pat. No. 6,748,046 to Thayer, the content of which is incorporatedherein by reference in its entirety.

Although certain embodiments are described herein with reference toinspection systems using X-ray energy, other embodiments may be appliedin other contexts including, but not limited to, inspection, imaging,and/or test systems employing X-rays or other suitable forms ofelectromagnetic energy.

With reference to FIG. 1, an X-ray inspection system according to oneembodiment is shown. The system includes an X-ray source 22 (such as,but not limited to, an X-ray tube) positioned opposite an X-ray detector24. In one embodiment, the detector 24 is a detection panel including aplurality of pixels. The detection panel may be generally flat. In aparticular embodiment, the detector 24 is composed of 2496×2304generally square-shaped pixels, each pixel having a length ofapproximately 50 μm.

An object that is to be inspected (or imaged) (see, for example, object231 of FIG. 2 and object 26, 46 of FIGS. 3A, 3B) is positioned at areconstruction plane (or image plane) 23 located between the source 22and the detector 24. With continued reference to FIG. 1, thereconstruction plane 23 is spaced at a distance Z1 from the focal spotof the source 22 and at a distance Z2 from the detector 24. Thedistances Z1, Z2 can be adjusted to suitably provide a desired field ofview (FOV) of the object. During inspection, a voltage (such as, but notlimited to, a voltage of approximately 110 kilovolts) and a current(such as, but not limited to, a current ranging from approximately 0.070milliamps to approximately 0.140 milliamps) are applied to the source 22for producing X-ray energy. Accordingly, the source 22 produces X-rayenergy, which penetrates or is absorbed by the object 231, andpenetrating X-ray energy is detected by one or more region(s) of thedetector 24.

With reference to FIG. 3A, according to one embodiment, the source 22can be moved to different positions (see, e.g., positions P1, P2, P3)with respect to object 26 to provide different views of the object 26.Here, the position of the object 26 is kept generally fixed, and thedistance Z1 is kept constant as the source 22 is moved. Although FIG. 3Ashows that the source 22 is moved generally along a first dimension(i.e., towards the left or the right in FIG. 3A), those skilled in theart will appreciate that the source 22 may also be moved generally alonga dimension perpendicular to the first dimension (i.e., a directionpointing out from or into the figure) to provide different views of theobject 26.

With reference to FIG. 3B, according to another embodiment, the source42 remains stationary, while the object 46 is moved generally along thedimensions described in the above paragraph (see, e.g., positions P1′,P2′, P3′). Similar to the embodiment of FIG. 3A, the detector 44 ispositioned opposite the source 42.

In certain embodiments, the detector 24, 44 is a solid-state device thatreceives the penetrating X-ray energy (including X-ray energy attenuatedby the object) and accordingly produces image data (such as, but notlimited to, grayscale image values). For example, each pixel of thedetector 24, 44 produces a grayscale value according to the energy thatit detects. The grayscale values may serve as an indicator of X-rayabsorption by the object. For example, a darker value may correspond toa lower amount of detected energy, which may indicate that acorresponding portion of the object is thicker and/or more absorbent.Conversely, a lighter value may correspond to a higher amount ofdetected energy, which may indicate that a corresponding portion of theobject is less thick and/or less absorbent. In certain embodiments, theoutput values are sent to an image processor and/or viewer forprocessing and/or viewing (see, for example, processor/viewer 30 in FIG.3A and processor/viewer 48 in FIG. 3B).

In certain embodiments, a beam monitoring device (see, for example, themonitoring device 32, 50 of FIGS. 3A, 3B) may be used in addition to, orin place of, the detector. In a particular embodiment, the beammonitoring device is a photodiode. Similar to the detector 24, 44, thebeam monitoring device is for detecting X-ray energy. In certainembodiments, the beam monitoring device is coupled with theprocessor/viewer 30, 48. As such, it is understood that measurementsprovided by the detector 24, 44, as described above, may also beprovided by the beam monitoring device.

With reference to FIG. 4, a flow diagram of a known calibration systemis shown. The calibration system is for calibrating systems including,but not limited to, X-ray inspection systems such as those describedabove.

Classical digital radiography techniques rely on X-ray flux todistinguish high contrast features. Tomosynthesis techniques rely onX-ray flux measurements taken from different angles (or views) to forman image using a density map of an object. Here, at each angle, theperformance of the measurement is essentially identical (or similar) totaking a conventional X-ray image. Both types of techniques, however,require a line integral of the resulting two-dimensional raw images,referred to herein as projections. Assuming that input X-ray photons aremono-energetic, an equation that relates the output X-ray energy (e.g.,the energy that has not been absorbed by an object and is detected bythe detector 24, 44) to that of the input X-ray energy (e.g., the energythat is produced by the source 22, 42 and incident on the object) is

I=I ₀ e ^(−μΔx).   (1)

In equation (1), I is the output X-ray energy, I₀ is the input X-rayenergy, Δx is the thickness of the inspected object (or a correspondingportion thereof), and μ is the linear attenuation coefficient (orabsorption coefficient) of the object material. The above equation, alsoknown as the Beer-Lambert law, expresses output energy as a function ofinput energy and the object material. Based on equation (1), it can beappreciated that materials having higher μ values produce higher levelsof X-ray attenuation relative to materials having lower μ values. Thehigher levels of X-ray attenuation result in lower output energy(assuming that input energy levels are equal in both cases). In the caseof air, the value of μ is approximately zero. Therefore, when the“object” positioned between an X-ray source and a detector is merelyair, the output energy I is theoretically equal to the input energy I₀because e⁰=1.

Where a non-uniform object is under examination (i.e., the object ismade of multiple materials having different attenuation coefficients),the overall attenuation characteristics can be modeled as follows. Ifthe object is considered as being composed of multiple (e.g., N)objects, each having a uniform thickness of Δx, the exit X-ray flux fromone object may be treated as the entrance X-ray flux to an adjacentobject. Mathematically, this model can be expressed as

$\begin{matrix}{I = {{I_{0}^{{- u_{1}}\Delta \; x}^{{- u_{2}}\Delta \; x}^{{- u_{2}}\Delta \; x}\mspace{14mu} \ldots \mspace{14mu} ^{{- u_{n}}\Delta \; x}} = {I_{0}{^{- {\sum\limits_{n = 1}^{N}{u_{n}\Delta \; x}}}.}}}} & (2)\end{matrix}$

Dividing both sides of equation (2) by I₀ and taking the negativenatural logarithm of both sides of the resulting equation produces:

$\begin{matrix}{\hat{p} = {{- {\ln \left( \frac{I}{I_{0}} \right)}} = {- {\sum\limits_{n = 1}^{N}{\mu_{n}\Delta \; {x.}}}}}} & (3)\end{matrix}$

In equation (3), {circumflex over (p)} is a mathematical representationof the two-dimensional image, or projection. As Δx approaches zero,{circumflex over (p)} approaches the integral of an attenuationcoefficient function over the length (or thickness) L of the object:

$\begin{matrix}{\hat{p} = {{- {\ln \left( \frac{I}{I_{0}} \right)}} = {- {\int_{L}{{\mu_{n}(x)}{{x}.}}}}}} & (4)\end{matrix}$

As such, equation (4) expresses the natural logarithm of the ratio ofthe output X-ray energy (or intensity) to the input X-ray energy as aline integral of the attenuation coefficients along the X-ray path.

Assuming that an X-ray beam is mono-energetic, an intensity C′(i,j), asdetected by a pixel of the detector 24, 44, can be expressed as:

$\begin{matrix}{{C^{\prime}\left( {i,j} \right)} = {{{S\left( {i,j} \right)}{P_{0}\left( {i,j} \right)}} - {\int_{p \in {path}}{{\mu \left( {x,y,z} \right)}{{p}.}}}}} & (5)\end{matrix}$

In equation (5), i and j respectively refer to the row and columncoordinate of the pixel in the detector, C′(i,j) represents (or isproportional to) the counts (e.g., grayscale value) produced by thepixel located at coordinates (i,j), μ(x,y,z) is the X-ray attenuationcoefficient of the object sample at each point between the X-ray sourceand the X-ray detector, and the integral is over the path p, whichrepresents the trajectory of the X-ray beam from the X-ray source to thedetector pixel. P₀(i,j) is the energy incident on the object sample,which is proportional to the drive current applied to the X-ray source.S(i,j) is the sensitivity of each detector pixel. It is assumed thatP₀(i,j) takes into account the anode heel effect and other propagationdistance variations of the system, and that the attenuation coefficientsμ(x,y,z) may span a wide range of materials, ranging from more densematerials including, but not limited to, copper, aluminum and lead toless dense materials including, but not limited to, air. However, thismodel does not consider the X-ray spot size, scatter, the detector pointspread function (PSF) and/or polyenergetic X-ray photons. Intomosynthesis digital imaging, several projections are taken of anobject, with the X-ray source placed at different positions (see, forexample, FIGS. 1 and 3A). These images may be denoted by C′_(n)(i,j),where positions of the source are denoted as X_(n), where n=1, 2, . . ., N.

Variations in pixel sensitivity may be corrected by a calibrationprocess, which can be mathematically expressed as

C _(n)(i, j)=G(i, j)C′ _(n)(i, j)   (6)

where G(i,j) is a gain calibration map or table and

$\begin{matrix}{{G\left( {i,j} \right)} = {\frac{1}{{S\left( {i,j} \right)}{P_{0}\left( {i,j} \right)}}.}} & (7)\end{matrix}$

The calibration procedure may generally correct for defective (orotherwise imperfect) pixels in the detector panel as well as forsituations in which S(i,j)=0 and correct for detector bias with acalibration dark image subtraction, as will be described in more detailbelow (see, for example, step 400 of FIG. 4). A parameter defined by

$\begin{matrix}{{I_{\log}\left( {i,j} \right)} = {{- \ln}\frac{G\left( {i,j} \right)}{C_{n}^{\prime}\left( {i,j} \right)}}} & (8)\end{matrix}$

is expressed as a logarithm such that signal components are additive andlinear processing methods can be utilized. The analysis here isperformed in the log domain to facilitate linear processing of signalsderived from the projections as defined by {circumflex over (p)} inEquation (4).

As previously noted, two-dimensional raw images produced by X-raysystems such as those described herein are referred to in thisdisclosure as projections. Projections may be calibrated (or corrected),for example, to remove artifacts including, but not limited to,undesirable artifacts of the X-ray imaging process. For example, theprojections can be field flattened and the image data linearized withrespect to thickness of object measured. Field flattening is performedto ensure that there is a more uniform representation of data at theedges (or edge portions) of the image relative to the center (or centerportions) of the image. As such, field flattening improves homogeneityof the image. However, such features may not be easily or readilyachievable or attainable due to characteristics of the X-ray beam, the1/r² effect (which is described in more detail, for example, in Doi,Suzuki and Hara, “Real-time X-ray Inspection of 3-D Defects in CircuitBoard Patterns,” IEEE Proceedings of the Fifth International Conferenceon Computer Vision, 1995, pages 575-582, the content of which isincorporated by reference in its entirety), the actual focal spot size,the anode heel effect, and the various propagation distances.

A known process for performing field flattening of an image is describedin more detail below. This process is described with reference to FIG. 4(see, for example, step 410 of FIG. 4).

If I(i,j) represents the 2-dimensional raw projection image (i.e., withi,j referring to a particular pixel of the detector and I(i,j) referringto the grayscale value produced by that pixel), then field flatteningyields a corrected image I_(corrected) that can be expressed as

I _(corrected)(i, j)=(I(i, j)−I _(dark)(i, j))×B(i, j)+Offset(i, j).  (9)

The subtraction of I_(dark)(i,j) is performed to correct or adjust fordark current that may exist in the particular X-ray sensor (or detector)used. The dark intensity is derived from one or more dark images, whichare taken, for example, at a drive voltage of around 0 kilovolts and adrive current of around 0 milliamps. As such, dark images are imagestaken in the absence of X-ray energy.

After the dark image correction is performed, then a digital gammacorrection may be performed (see, for example, step 420 in FIG. 4). Withcontinued reference to equation (9), B(i,j) refers to a gain valuecomputed by shooting X-rays at a known energy (e.g., at a known drivevoltage and drive current) through multiple plates of a known material(e.g., stainless steel) one plate at a time. The plates have differentthicknesses with respect to one another. For example, three differentplates can be used (e.g., a plate of a lower thickness, one of a mediumthickness, and one of a higher thickness). For example, respectivethicknesses of the plates can be 15 mils, 30 mils, and 90 mils. Oncemeasurements have been taken of the different plates using the X-rays ofa known energy, the results can be used to derive a linear curve fit.The linear curve fit is derived to approximate the non-linear responseof X-ray intensity with respect to the thickness of the sample measured.That is, the relationship between the intensity values and the thicknessof the inspected object can be approximated by a linear equation of theform y=mx+c (see, for example, equation (9) above). In such an equation,m is the slope of the curve and c is the y-offset.

The I_(corrected)(i,j) projection image can be further processed usingstandard image processing techniques. One such technique is known asgamma processing. Here, the corrected projection image is input into agamma function. The result is an image having a more uniform variationof intensity within a given grayscale range. Mathematically, suchprocessing can be represented by the equation:

I _(γcorrected)(i, j)=γ_(index)(I _(corrected)(i, j)).   (10)

Further corrections can also be made. For example, if one or more pixelsof a digitizing X-ray sensor are known in advance to be defective (orotherwise imperfect) (in some situations, a map may be providedidentifying such pixels), these pixels can be corrected for. Forexample, an image value can be ascribed to a defective pixel, where theascribed value is based on a weighted interpolation of neighboringpixels. Such correction may be useful in that values in the projectiondata, that are produced by defective pixels, can be removed andreplaced. The resulting corrected image is referred to herein asI_(final)(i,j).

I _(final)(i, j)=Detector correction(I _(γcorrected) (i, j))   (11)

However, field flattening using digital gamma techniques, such as thosedescribed above, may not be effective or sufficiently effective. Forexample, as previously described, these techniques involve sequentiallymeasuring different inspection samples, such as plates of metal havingthicknesses that are different from one another. This may requiredriving the X-ray source at different current levels to betterfacilitate measuring of the different plates. For example, measuring athicker sample may require that a higher current be applied to the X-raysource so that more meaningful results can be obtained (for example,X-ray energy produced using a current of an insufficient magnitude mightbe fully absorbed by such a sample). These techniques may also beproblematic because the system response is not linear with thickness.For example, although a thicker portion of a sample may produce a higherlevel of absorption of X-ray energy, the level of absorption may benonlinear with respect to the thickness of the sample.

In addition, curve fitting using the gamma technique may not beintuitive and is empirically determined to a larger extent than it ismathematically determined. Further, calibrating using the digital gammatechnique may require that the calibration process be repeated at ahigher frequency—e.g., once a day after warm up, at each manufacturingshift change, etc. In addition, because the digital gamma technique doesnot correct for flux variations, it may be necessary to tune thetechnique in accordance with a specific system.

In embodiments of the present invention, an “air calibration” isperformed, as will be described in more detail below (see, for example,step 510 in the generalized inverse log transform (GILT) process of FIG.5). In some embodiments, the air calibration is performed at a processorsuch as processor 30, 48 of FIGS. 3A, 3B. The air calibration may beused in place of the known digital gamma technique. The air calibrationtechnique performs field flattening of images more effectively—e.g., ineliminating (or at least partially reducing) the 1/r² effect previouslydescribed. As noted previously, field flattening is performed to rendermore uniform representation of data at edges of the image as well as atthe center of the image.

As also noted previously, improving the homogeneity of images may not beeasily achievable due to factors including the characteristics of theX-ray beam, the curved nature of the flat panel detectors, the actualfocal spot size, the anode heel effect and the various propagationdistances. As will be described in more detail below, an “air table” isproduced (e.g., based on images produced according to the systemconfiguration of FIG. 1) to eliminate or at least reduce the impacts ofthe 1/r² effect. According to embodiments of the present invention,values of the air table capture systematic errors which are present inimages produced by the system. These images include “air images,” aswell as images of an object under inspection. Subtracting values of theair table from the inspection images effectively eliminates or at leastreduces the effects of systematic errors in the system. Flux correctionon the other hand is handled separately and is described in more detailbelow.

Calibrating inspection images using the values of the air table, as willbe described in more detail below, may correct for instability in thesource (or tube) output, which may occur during an inspection. Inaddition, such calibration may correct for source instabilities thatarise during the operating lifetime of the source. These adjustments arebased on the premise that systematic errors resulting from behavior suchas, but not limited to, fluctuations of the tube, voltage, current orother system instabilities can be captured in the air table values andcan be effectively removed via processing (e.g., performing mathematicaloperations).

According to one embodiment, the calibration technique involves buildingan air table consisting of air reference values. In a furtherembodiment, each of the reference values corresponds to an individualpixel of the detector panel. As such, in a panel having 2496×2304pixels, the air table may include 2496×2304, or 5,750,784 values.

According to one embodiment, the calibration of a system (e.g., thesystem shown in any of FIGS. 1, 2, 3A, 3B) includes taking an air imageusing the system. An air image is an image taken with no object (e.g.,no material other than air) positioned in the path of the X-ray beam(s),from the source to the detector—hence, the term “air image.” The airimage effectively captures effects of systematic errors on the imagesproduced by the system. Processing images taken by the system (e.g., ofone more actual objects positioned between the source and the detector)based on the air images—e.g., by subtracting air image grayscale valuesfrom those of the images—eliminates (or at least partially reduces) theeffects of the systematic errors. In one embodiment, the air imagegrayscale values are collected in a table for processing of the images.

Because no object is placed between the source and the detector inproducing the air images, the air images may be produced using agenerally constant drive current and/or drive voltage. This may becontrasted with the digital gamma techniques described previously, whichinvolved driving a X-ray source at different levels to better facilitatethe imaging of sample plates having thicknesses different relative toone another.

In one embodiment, the calibration images are air images that are takenat one set of settings generally the same as the set of settings thatare used subsequently to take acquisition images—i.e., images of actualobjects. However, in other embodiments, the calibration images are takenat a set of settings different from the set of settings used to take theacquisition images.

For example, according to one embodiment, one such setting is the drivecurrent that is applied to the X-ray source. In order to provide ahigher-quality image when an actual object is being imaged, theacquisition images are taken at a drive current higher than that used intaking the calibration images. In addition, it may be desirable to takethe calibration images using a lower drive current in order to avoidpotentially over-saturating the detector.

According to another embodiment, a setting that is varied in taking thecalibration images and the acquisition images is the frame integrationsetting, i.e., the number of frames (or actual snapshots) that compose asingle image. The frame integration setting may also be specified interms of milliseconds (i.e., the spacing in time in between consecutiveframes). Here, it is understood that taking multiple frames andprocessing the frames (e.g., by averaging them out) to produce a singleimage may serve to produce images that are less noisy. For example,according to one embodiment, in order to provide a higher-quality (e.g.,less noisy) image when an actual object is being imaged, the acquisitionimages are taken at a frame integration setting higher (i.e., moreframes are used to compose a single image) than that used in taking thecalibration images. Here, it is contemplated that taking multiple framesand processing the frames (e.g., by averaging them out) to produce asingle image may serve to produce images that are less noisy.

In embodiments such as those described above where settings (such asdrive current and/or frame integration) are changed in between takingthe calibration images and the acquisition images, the values of the airtable are modified according to the changes in the settings. In afurther embodiment, the values of the air table are created bymultiplying the grayscale values of the air images by (1) a ratio of thedrive current used to take the acquisition images to the drive currentused to take the air images and (2) a ratio of the frame integrationused to take the acquisition images to the frame integration used totake the air images.

In still another embodiment, where settings (such as drive currentand/or frame integration) are changed in between taking the calibrationimages and the acquisition images, the air table values are calculateddifferently. Here, the air images include two images: one image taken atthe first set of settings and another image taken at the second set ofsettings. In a further embodiment, the values of the air table arecreated by dividing the grayscale values corresponding to the images ofthe first set of settings by the grayscale values corresponding to theimages of the second set of settings.

Although settings such as the drive current and the frame integrationmay be configured differently, as described above, the Z1 and Z2distances (see, for example, FIGS. 1 and 2A) are kept generally constantwhile taking both the inspection images and the air images.

In an exemplary embodiment, calibration of a system is performed asfollows:

The air calibration can be mathematically modeled as:

I′ ₀=ln(I ₀),   (12)

where I₀ is the air image (i.e., the collection of grayscale values thatcompose the image) obtained by shooting X-ray energy through air (see,e.g., the system configuration as shown in FIG. 1).

The air image I₀ is taken at a drive current level mA_(air) (in units ofmicroamps) and at a frame integration value of FI_(air) (in units ofnumber of frames). A flux parameter I_(mo) during an air shot can bedetermined as the product of the drive current level and the frameintegration value. That is,

I _(mo)=mA_(air)×FI_(air).   (13)

As previously described, the air images may be taken at a set ofsettings different from the set of settings used to take acquisitionimages (referred to below as I). For example, acquisition images may betaken at a drive current level mA_(insp) and at a frame integrationvalue of FI_(insp), one or more of which may be respectively differentfrom (e.g., greater than) mA_(air) and FI_(air). As such, a fluxparameter value I_(m) can be determined as the product of the drivecurrent level and the frame integration value. That is,

I _(m)=mA_(insp)×FI_(insp).   (14)

According to a further embodiment, the parameter I_(flux) is determinedto account for potential differences in one or more of the settingsdescribed above:

$\begin{matrix}{I_{flux} = {\frac{{mA}_{insp} \times {FI}_{insp}}{{mA}_{air} \times {FI}_{air}} = {\frac{I_{m}}{I_{mo}}.}}} & (15)\end{matrix}$

As such, values of the air table can be calculated as:

I′ _(0 flux) =I′ ₀ ×I _(flux)=ln(I ₀)−ln(I _(mo))+ln(I _(m))   (16)

It is understood that the calculation of equation (16) accounts forpotential differences in the settings used to take the air images andthe acquisition images. Here, it is noted that if the settings used arenot changed (e.g., I_(m) is generally equal to I_(mo)), then the valuesof the air table are equal to the grayscales of the air image I₀.

As previously noted, an air image may be modeled as the naturallogarithm of the grayscale values that make up the air image. Similarly,an acquisition image may be modeled as the natural logarithm of thegrayscale values that make up the acquisition image. That is,

I′=ln(I),   (17)

where I is the image obtained upon positioning an object between thesource and the detector (see, for example, the configuration shown inFIG. 2).

According to one embodiment, the acquisition image is calibrated usingthe values of the air table. In one exemplary embodiment, the values ofthe air table are subtracted from the grayscale values of theacquisition image. That is,

I _(calibrated) =I′ ₀ −I′=ln(I ₀)−ln(I _(mo))+ln(I _(m))−ln(I).   (18)

Here, the reverse of the sign in equation (18) is due to the inverseabsorption equation from equation 1.

As previously described, with reference to another embodiment, wheresettings (such as drive current and/or frame integration) are changed inbetween taking the calibration images and the acquisition images, airtable values may be calculated differently. Here, the air images includetwo images: one image taken at the first set of settings and anotherimage taken at the second set of settings. The calculation will bedescribed in more detail below.

As described, embodiments of the present invention are directed to asoftware-based technique that is more cost effective. However,embodiments of the present invention are not limited thereto. Forexample, in other embodiments, a hardware modification may beimplemented in the system by placing a hardware element, such as (butnot limited to) a reference monitor or a photodiode, in the system (see,for example, the monitoring device 32, 50 of FIGS. 3A, 3B). The hardwarecomponent is for constantly (or periodically) monitoring the tube outputover a period of time, both during calibration as well as during aninspection. Placement of such a hardware monitor may also be effectivein eliminating “systematic errors.” As such, embodiments of the presentinvention also contemplate positioning hardware monitors in the system(e.g., adjacent to the X-ray source).

According to one embodiment, the building of the air table is based on amathematical model of X-ray radiation as opposed to an empiricallydetermined solution. The air table is used to perform the fieldflattening. According to an exemplary embodiment, the air tables arebuilt when there is a change in the inspection geometry such as, but notlimited to, changes to the Z1 and Z2 distances. This approach may becontrasted with the known approach, where a digital gamma table isrequired to be built for every single exposure setting.

According to described embodiments, the technique eliminates systeminstability caused by using different exposure settings, which wasrequired in the known technique. This is because certain elements (orartifacts) can be removed from the processed image.

Accordingly, the useful life of the X-ray source can potentially belengthened. In more detail, using known techniques, the tube may bereplaced earlier than necessary because data produced by the system arenot compensated to account for fluctuations of the source over itslifetime. That is, there is no reference correction. The fluctuation inthe tube over its lifetime may lead to differences in produced grayscalevalues. This, in turn, may lead to differences in inspection results,which may then lead to a higher false calls rate. A user may correlatethe higher false call rates to depreciation of tube life, which, inactuality, may not be fully accurate.

Embodiments of the current invention use a reference correction tocompensate for the tube output fluctuations, thereby potentiallyprolonging the useful life of the tube. In addition, the use of multiplereference plates, as described with reference to known techniques, iseliminated.

One feature of embodiments of the present invention is better imagequality over other systems in the field. Another feature is that tubelife can be extended due to software compensation, thereby reducingreplacement unit costs. Another feature is reduced variability acrossresults from machine to machine, e.g., from 25% to less than 3%.

Because system-to-system stability can been achieved using embodimentsof the present invention, these embodiments may be useful inapplications where Gauge Rand R requirements for machine-to-machinevariability have extremely tight tolerances. Another feature is improvedtemporal stability.

Known techniques (such as those using multiple calibration sheets)involve building a table for every geometry change (e.g., Z1 & Z2).These known techniques are limited in the number of fields of viewpossible, given the calibration data.

According to embodiments of the present invention, an approach iscontinuous in that a field of view can be chosen and an air tableprepared accordingly. For example, according to one embodiment, onefield of view (FOV) may be chosen, and air images may be taken at onedrive level, producing one air table. According to another embodiment,one FOV is selected, and air images are taken at five different drivecurrent levels, thereby producing 5 tables. This may be repeated for anumber of different fields of view, to prepare more tables. For example,assuming four FOVs, 20 tables may be prepared.

As previously described, known imaging techniques are based on theassumption that a difference in grayscale level reflects a difference inthickness level of object under inspection. This is incorrect insofar asthe relationship between the thickness of the object inspected and thegrayscale level is non-linear. As such, in embodiments of the presentinvention, the relationship between grayscale and thickness of theinspected object may be linearized according to the disclosure ofco-pending U.S. application co-pending U.S. patent application Ser. No.______ filed on the same date herewith entitled “Method of and Systemfor Obtaining Linear Data for Object Scanned Using Non-Collimated,Polyenergetic X-ray Beams” and designated as Docket No. 073311-0179(2146) in the law offices of Foley & Lardner LLP, the contents of whichare incorporated herein by reference.

According to an exemplary embodiment of the present invention, a processfor calibrating images includes the following:

1. An air image I_(air) ^(raw)(i, j) is taken. An air image may bedefined as a 2-D transmission image acquired at distances Z1 and Z2separating a reconstruction plane from the source and from the detector,respectively. In a particular embodiment, the air image is taken at avoltage of 110 kV and a current of 0.070 mA applied to the source. Aspreviously described, the X-ray energy generated from the source travelsto the detector with no object in the beam path (see, for example, theconfiguration of FIG. 1). Multiple images (e.g., N images) may be taken.

2. Acquire one or more dark images I_(dark)(i, j). A dark image may bedefined as an image taken without using X-ray energy (e.g., at a drivevoltage of around 0 kilovolts and a drive current of around 0 milliampsapplied to the X-ray source). Here, according to one embodiment, thenumber of dark images taken is equal to the number of air imagesacquired (N).

3. In a further embodiment, the images above are cropped and/or flipped(or rotated). For example, an image may be cropped from an original sizeof 2396×2404 pixels to a cropped size of 2192×2192 pixels. Here, theportion of the image produced by certain pixels is cropped to removecertain portions of the image such as (but not limited to) peripheralportions of the image for ease of later processing, reductions incomputational load, etc. In one embodiment, the image is also flipped(or rotated) about a certain axis (e.g., vertical or horizontal). Here,the image is manipulated for providing a certain or desired orientationthat may not have been provided by the imaging configuration.

4. The dark images are then subtracted from the air images as follows:

$\begin{matrix}{{I_{air}\left( {i,j} \right)} = {{\sum\limits_{n = 1}^{N}{I_{air}^{raw}\left( {i,j} \right)}_{n}} - {{I_{dark}\left( {i,j} \right)}_{n}.}}} & (19)\end{matrix}$

5. According to one embodiment, a reference factor I_(ref) is computed.The reference air value is computed, for example, to account forpotential difference(s) in settings used in taking the air images andlater inspection images.

(a). Here, according to a particular embodiment, I_(ref) is computed asa ratio of (1) settings used to take subsequent inspection images to (2)settings used to take the above air images. For example, if inspectionimages are taken at a drive current level of mA_(insp) and a frameintegration value of FI_(insp) and if air images are taken at a drivecurrent level of mA_(air) and a frame integration value of FI_(air),then I_(ref) may be computed as:

$\begin{matrix}{I_{ref} = {\frac{{mA}_{insp} \times {FI}_{insp}}{{mA}_{air} \times {FI}_{air}}.}} & (20)\end{matrix}$

(b) According to another embodiment, I_(ref) is computed using airimages taken at one set of settings and a second set of settings that isused to take subsequent inspection images. For example, if inspectionimages are taken at a drive current level of mA_(insp) and a frameintegration value of FI_(insp) and if air images are taken at a drivecurrent level of mA_(air) and a frame integration value of FI_(air),then I_(ref) may be computed as a ratio of (1) air images taken at the(mA_(insp), FI_(insp)) settings to (2) air images taken at the(MA_(air), FI_(air)) settings. For example, according to one embodiment,I_(ref) may be computed as:

$\begin{matrix}{I_{ref} = {\frac{f\left( {images}_{insp\_ settings} \right)}{f\left( {images}_{air\_ settings} \right)}.}} & (21)\end{matrix}$

According to one embodiment, the numerator of the ratio in equation (21)is produced by calculating a representative grayscale valuecorresponding to a certain number of pixels in the air images taken atthe inspection settings. Similarly, the denominator of the ratio inequation (21) is produced by calculating a representative grayscalevalue corresponding to a certain number of pixels in the air imagestaken at the air settings. According to a particular embodiment, therepresentative grayscale value is an average grayscale valuecorresponding to a subset of the pixels. For example, the subset mayinclude approximately 100,000 pixels, which may generally correspond toa central region of the images produced.

7. Reference air image values are then computed by multiplying the abovereference factor by the air image values:

I _(air) ^(ref)(i, j)=I _(ref) ×I _(air)(i,j).   (22)

8. The air table values are then computed by taking the naturallogarithm of the reference air image values (see equation (24) below).According to a further embodiment, before the natural logarithm of thevalues is performed, values less than or equal to 1 are set to a defaultvalue of 1 (see equation (23) below) to compensate for underflowsituations (e.g., insufficiently high readings).

$\begin{matrix}{{I_{air}^{ref}\left( {i,j} \right)} = \begin{Bmatrix}{1,} & {{I_{air}^{ref}\left( {i,j} \right)} \leq 1} \\{{I_{air}^{ref}\left( {i,j} \right)},} & {otherwise}\end{Bmatrix}} & (23) \\{{I_{air}^{{table}\; \log}\left( {i,j} \right)} = {\ln \; {I_{air}^{ref}\left( {i,j} \right)}}} & (24)\end{matrix}$

As described above, the calculation of reference air image values isdescribed with reference to exemplary embodiments. The calibration ofinspection images according to reference air image values is describedin more detail below, with reference to an exemplary embodiment.

1. An inspection image I_(raw)(i, j) is acquired. Here, an inspectionimage can be defined as a 2-D transmission image acquired at an imagingplane located at distances Z1 and Z2 separating a reconstruction planefrom the source and from the detector, respectively. A certain voltageand current (e.g., 110 kV, 0.070 mA) is applied to the source togenerate X-ray energy. An object under inspection is placed in the pathof the beams along the reconstruction plane. Multiple images (e.g., N)may be acquired.

2. Multiple N dark images I_(dark)(i, j) are acquired. As previouslydescribed, a dark image is taken in the absence of X-ray energy.

3. In one embodiment, the above images are cropped and/or flipped. Forexample, as described previously, the images may be reduced from anoriginal size of 2396×2404 pixels to a cropped size of 2192×2192 pixels.As another example, the image may also be flipped (or rotated) about acertain axis (e.g., the x-axis).

4. The dark images are then subtracted from the inspection images asfollows:

$\begin{matrix}{{I_{raw}\left( {i,j} \right)} = {{\sum\limits_{n = 1}^{N}{I_{raw}\left( {i,j} \right)}_{n}} - {I_{dark}\left( {i,j} \right)}_{,}}} & (25)\end{matrix}$

5. The images are further processed by taking the natural logarithm ofthe inspection images (see equation (27) below). According to a furtherembodiment, before the natural logarithm of the images is performed,values less than or equal to 1 are set to a default value of 1 (seeequation (26) below) to compensate for underflow (e.g., insufficientlyhigh) readings.

$\begin{matrix}{{I_{raw}\left( {i,j} \right)} = \begin{Bmatrix}{1,} & {{I_{raw}\left( {i,j} \right)} \leq 1} \\{{I_{raw}\left( {i,j} \right)},} & {otherwise}\end{Bmatrix}} & (26) \\{{I_{raw}^{\log}\left( {i,j} \right)} = {\ln \; {I_{raw}\left( {i,j} \right)}}} & (27)\end{matrix}$

6. The images are then calibrated according to the air table valuesdescribed above. For example, according to one embodiment, the naturallogarithm of the images is subtracted from the air table values toproduce the calibrated image values.

I _(aircor) ^(log)(i, j)=I _(air) ^(table log)(i, j)−I _(raw) ^(log)(i,j)   (28)

7. According to embodiments where the X-ray energy produced by thesource is non-collimated, the calibrated images are linearized such thata linear relationship between the calibrated grayscale values andthickness of the object under inspection is obtained. Such linearizationis disclosed in more detail in co-pending U.S. patent application Ser.No. ______ filed on the same date herewith entitled “Method of andSystem for Obtaining Linear Data for Object Scanned UsingNon-Collimated, Polyenergetic X-ray Beams” and designated as Docket No.073311-0179 (2146) in the law offices of Foley & Lardner LLP. Thisco-pending application is owned by the Assignee of the presentapplication, and the entire contents of the co-pending application areincorporated herein by reference. As described in more detail in theco-pending application, the data is linearized by using the followingformulations:

I _(aircor) ^(nocoll)(i, j)=(I _(air) ^(table log)(i, j)−I _(raw)^(log)(i, j))²   (29) or

I _(aircor) ^(nocoll)(i, j)=(I _(aircor) ^(log)(i, j))²   (30)

8. Finally, according to a further embodiment, the linearized image dataare scale appropriately for analysis by existing classificationalgorithms. Classification algorithms or detection algorithms aremathematical processes (e.g., processes that may be implemented insoftware) which may use the corrected X-ray image as input and analyzethe input in order to find defects such as, but not limited to, opens,bridges, voids, etc. in the components on the printed circuit board.According to one such classification algorithm, equation (31) isemployed:

I _(aircor) ^(scale)(i, j)=I _(white) −I _(aircorr) ^(nocoll)(i, j)×S_(c),   (31)

where I_(white)=4095 S_(c) is a scale factor that may be empiricallydetermined.

Embodiments of the present invention are directed to asoftware-implemented correction approach for calibrating imaging systemsin a cost- and time-efficient manner. According to certain embodiments,tube life can be extended due to software compensation, thereby reducingfield replacement unit costs.

It should be understood that various modifications may be made to theembodiments disclosed herein. Therefore, the above description shouldnot be construed as limiting, but merely as exemplification of thevarious embodiments. By way of example, other embodiments may be usedfor imaging assemblies for purposes other than inspection and qualitycontrol. Those skilled in the art will envision other modificationswithin the scope and spirit of the claims appended thereto.

1. A calibration system for calibrating image data produced by animaging device, the calibration system comprising: a processorconfigured for: receiving the image data from the imaging device;receiving a plurality of reference values from the imaging device; andcalibrating the image data using the reference values, wherein thereference values correspond to air image data produced by the imagingdevice.
 2. The calibration system of claim 1, wherein the processor isconfigured for calibrating the image data by subtracting the referencevalues from the image data.
 3. The calibration system of claim 1,wherein the image data correspond to an image of one or more objects,and wherein the air image data are produced by the imaging device freeof the one or more objects.
 4. The calibration system of claim 1,wherein the image data and the air image data are produced by theimaging device using imaging energy detected by a detector of theimaging device, wherein the one or more objects are positioned adjacentthe detector to produce the image data, and wherein the one or moreobjects are not positioned adjacent the detector to produce the airimage data.
 5. The calibration system of claim 4, wherein the imagingenergy comprises X-ray energy.
 6. The calibration system of claim 1,wherein the image data are produced by the imaging device according to afirst drive current, wherein the air image data are produced by theimaging device according to a second drive current, and wherein thefirst drive current is higher in amplitude than the second drivecurrent.
 7. The calibration system of claim 1, wherein the image dataare produced by the imaging device according to a first frameintegration level, wherein the air image data are produced by theimaging device according to a second frame integration level, andwherein the first frame integration level is higher than the secondframe integration level.
 8. A calibration system for calibrating imagedata produced by an imaging device, the calibration system comprising:means for receiving the image data from the imaging device; means forreceiving a plurality of reference values from the imaging device; andmeans for calibrating the image data using the reference values, whereinthe reference values correspond to air image data produced by theimaging device.
 9. The calibration system of claim 8, wherein the meansfor calibrating is configured for calibrating the image data bysubtracting the reference values from the image data.
 10. Thecalibration system of claim 8, wherein the image data correspond to animage of one or more objects, and wherein the air image data areproduced by the imaging device free of the one or more objects.
 11. Thecalibration system of claim 8, wherein the image data and the air imagedata are produced by the imaging device using imaging energy detected bya detector of the imaging device, wherein the one or more objects arepositioned adjacent the detector to produce the image data, and whereinthe one or more objects are not positioned adjacent the detector toproduce the air image data.
 12. The calibration system of claim 11,wherein the imaging energy comprises X-ray energy.
 13. The calibrationsystem of claim 8, wherein the image data are produced by the imagingdevice according to a first drive current, wherein the air image dataare produced by the imaging device according to a second drive current,and wherein the first drive current is higher in amplitude than thesecond drive current.
 14. The calibration system of claim 8, wherein theimage data are produced by the imaging device according to a first frameintegration level, wherein the air image data are produced by theimaging device according to a second frame integration level, andwherein the first frame integration level is higher than the secondframe integration level.
 15. A method for calibrating image dataproduced by an imaging device, the method comprising: receiving theimage data from the imaging device; receiving a plurality of referencevalues from the imaging device; and calibrating the image data using thereference values, wherein the reference values correspond to air imagedata produced by the imaging device.
 16. The method of claim 15, whereincalibrating the image data comprises subtracting the reference valuesfrom the image data.
 17. The method of claim 15, wherein the image datacorrespond to an image of one or more objects, and wherein the air imagedata are produced by the imaging device free of the one or more objects.18. The method of claim 15, wherein the image data and the air imagedata are produced by the imaging device using imaging energy detected bya detector of the imaging device, wherein the one or more objects arepositioned adjacent the detector to produce the image data, and whereinthe one or more objects are not positioned adjacent the detector toproduce the air image data.
 19. The method of claim 18, wherein theimaging energy comprises X-ray energy.
 20. The method of claim 15,wherein the image data are produced by the imaging device according to afirst drive current, wherein the air image data are produced by theimaging device according to a second drive current, and wherein thefirst drive current is higher in amplitude than the second drivecurrent.